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@OpenAI
Apr 6, 2022 • 8 tweets • 5 min read • Read on X
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Here’s a look at what DALL·E 2 can do. 👀🧵👇

Want to see more? Follow along on Instagram: instagram.com/openaidalle/
“A Shiba Inu dog wearing a beret and black turtleneck” #dalle
“A sea otter in the style of ‘Girl with a Pearl Earring’ by Johannes Vermeer.” #dalle
“Teddy bears mixing sparkling chemicals as mad scientists” in the style of steampunk, a 1990s Saturday morning cartoon, and digital art #dalle
“An ibis in the wild, painted in the style of John Audubon” #dalle
“A bowl of soup that looks like a monster” knitted out of wool, made of plasticine and spray painted on a wall #dalle
“A photo of a quaint flower shop storefront with a pastel green and clean white facade and open door and big window” #dalle
“A photo of an astronaut riding a horse” #dalle

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More from @OpenAI

OpenAI Profile picture
Feb 5
We worked with @Ginkgo to connect GPT-5 to an autonomous lab, so it could propose experiments, run them at scale, learn from the results, and decide what to try next. That closed loop brought protein production cost down by 40%.
GPT-5 was connected to an autonomous lab: it designed experiments, the lab executed them, and the results informed the next designs across six iterations.

In this setup, GPT-5 designed batches of experiments, the lab executed them, and the data fed back into the next round. We repeated that cycle six times, exploring 36,000+ reaction compositions across 580 automated plates.Image
We found that the improvements came from identifying combinations that work well together and that hold up in the realities of high-throughput automation.

GPT-5 identified low-cost reaction compositions that humans had not previously tested in this configuration. Cell-free protein synthesis (CFPS) has been studied for years, but the space of possible mixtures is still large. When you can propose and execute thousands of combinations quickly, you can find workable regions that are easy to miss with a manual workflow.
Read 4 tweets
OpenAI Profile picture
Jan 27
Introducing Prism, a free workspace for scientists to write and collaborate on research, powered by GPT-5.2.

Available today to anyone with a ChatGPT personal account: prism.openai.com
Prism offers unlimited projects and collaborators in a single, cloud-based, LaTeX-native workspace.

GPT-5.2 works inside your project with access to paper structure, equations, references, and surrounding context—right where the work happens. Image
Prism removes version conflicts and setup overhead—making powerful scientific tools easier to adopt and more accessible to researchers everywhere.

openai.com/prism
Read 4 tweets
OpenAI Profile picture
Jan 16
In the coming weeks, we plan to start testing ads in ChatGPT free and Go tiers.

We’re sharing our principles early on how we’ll approach ads–guided by putting user trust and transparency first as we work to make AI accessible to everyone.

What matters most:
- Responses in ChatGPT will not be influenced by ads.

- Ads are always separate and clearly labeled.

- Your conversations are private from advertisers.

- Plus, Pro, Business, and Enterprise tiers will not have ads.Image
Here's an example of what the first ad formats we plan to test could look like. Image
Facts about the ads test in ChatGPT: Image
Read 4 tweets
OpenAI Profile picture
Jan 7
Introducing ChatGPT Health — a dedicated space for health conversations in ChatGPT. You can securely connect medical records and wellness apps so responses are grounded in your own health information.

Designed to help you navigate medical care, not replace it.

Join the waitlist to get early access.

openai.com/index/introduc…
ChatGPT Health can help you navigate everyday questions and spot patterns over time, so you feel more informed, prepared, and confident for important medical conversations.
If you choose, ChatGPT Health lets you securely connect medical records and apps like Apple Health, MyFitnessPal, and Peloton to give personalized responses.
Read 6 tweets
OpenAI Profile picture
Dec 18, 2025
To preserve chain-of-thought (CoT) monitorability, we must be able to measure it.

We built a framework + evaluation suite to measure CoT monitorability — 13 evaluations across 24 environments — so that we can actually tell when models verbalize targeted aspects of their internal reasoning. openai.com/index/evaluati…
Monitoring a model’s chain-of-thought is far more effective than watching only its actions or final answers.

The more a model “thinks” (longer CoTs), the easier it is to spot issues. Image
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RL at today’s frontier doesn’t seem to wreck monitorability and can help early reasoning steps. But there’s a tradeoff: smaller models run with higher reasoning effort can be easier to monitor at similar capability — at the cost of extra inference compute (a “monitorability tax”).
Read 5 tweets
OpenAI Profile picture
Dec 16, 2025
Accelerating scientific progress is one of the most impactful ways AI can benefit society. Models can already help researchers reason through hard problems — but doing this well means testing models on tougher evaluations and in real scientific workflows grounded in experiments.
We’re releasing a new eval to measure expert-level scientific reasoning: FrontierScience.

This benchmark measures PhD-level scientific reasoning across physics, chemistry, and biology.

It contains hard, expert-written questions (both olympiad-style problems and longer research-style tasks) designed to reveal where models succeed and where they fall short.
openai.com/index/frontier…
GPT-5.2 is our strongest model on the FrontierScience eval, showing clear gains on hard scientific tasks.

But the benchmark also reveals a gap between strong performance on structured problems and the open-ended, iterative reasoning that real research requires. Image
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Read 7 tweets

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